Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does well: it discloses data provenance (Eurostat COMEXT), coverage limits (EU27 reporters, HS2 only), freshness ('verified 2026-08-27'), a key caveat that 'EU-wide CN8 must not be inferred', and that supported filters vary by REST view, plus a data-coverage URL. It does not state pagination/limit behavior, but the constraint disclosures are substantive beyond a bare description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the core capability ('Sputnik X EU trade intelligence — query 67.7M Eurostat COMEXT rows') before constraints and caveats, and nearly every clause carries information. It is dense — semicolon-chained coverage facts and a provenance timestamp — so it reads as packed rather than flowing, but little is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a nine-parameter tool with no output schema and no annotations, the description covers scope, coverage limits, and a critical inference caveat well. It is incomplete on the dimension that matters most here: eight distinct query types are named but none is explained, so an agent cannot tell what results to expect from each, and return shape is unaddressed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds only marginal parameter meaning — it reinforces that hs2 is two-digit-only ('97 two-digit codes') and lists query_type values already in the enum — while saying nothing specific about how flow, partner, reporter, years, or response_format interact with the query types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource with concrete scope: 'query 67.7M Eurostat COMEXT rows', naming the dataset, reporter scope (EU27), time span (2005-01–2026-06), and granularity (HS2 only, 97 codes). An agent immediately knows this is Eurostat trade-intelligence querying and can distinguish it from every sibling tool, none of which touch trade data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Enumerates the eight query types (overview, countries, timeline, top_partners, top_products, balance, heatmap, macro_context) and briefly labels macro_context as a 'current global ECB/FRED snapshot', which implies usage. However, it never explains what each type returns or when to choose one over another, and gives no explicit when-not-to-use guidance; usage is implied rather than directed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.